Rail transit monitoring information playback method, device, equipment, medium and product

Abstract

The application discloses a rail transit monitoring information playback method and device, equipment, medium and product, and relates to the technical field of data processing. The method comprises the following steps: reading a target line number and a playback time period from a received historical playback instruction; obtaining a plurality of historical rail transit data matched with the line number and the playback time period from a pre-constructed time sequence database table; wherein the historical collection time of the historical rail transit data is within the playback time period, and the historical rail transit data at least comprises historical ATS train operation monitoring data, historical ATS equipment monitoring data, historical integrated monitoring system monitoring data, historical passenger flow monitoring data and historical operation organization adjustment data; and sequentially outputting the plurality of historical rail transit data from early to late according to the historical collection time. The application effectively improves the efficiency and accuracy of fault judgment, and further improves the efficiency and accuracy of fault judgment of operation management personnel.

Description

Technical Field

[0001] This application relates to the field of data processing technology, and in particular to a method, apparatus, equipment, medium and product for playing back rail transit monitoring information. Background Technology

[0002] In the urban rail transit operation and management system, operation monitoring, as a core business link, plays a vital role in ensuring the safe, efficient, and stable operation of rail transit.

[0003] In the field of train monitoring, historical playback functionality has become an indispensable tool for in-depth review of the occurrence of faults or anomalies. Currently, signal manufacturers typically employ specific technical solutions to implement the playback function of train monitoring systems: real-time data received from the Automatic Train Supervision (ATS) system is recorded into files, and these recorded files are loaded and decoded for playback when needed.

[0004] However, the current monitoring services of the rail network center cover many aspects besides train operation monitoring, including equipment monitoring, passenger flow monitoring, and operational organization monitoring. These different types of monitoring services each correspond to a variety of data sources. Because the acquisition and storage processes of each data source are independent, historical playback requires calling up and playing back the record files from different data sources separately. This makes it difficult to intuitively reflect the actual operating conditions of the rail transit at the time, thus affecting the efficiency and accuracy of operation management personnel in diagnosing faults. Summary of the Invention

[0005] The purpose of this application is to provide a method, device, equipment, medium and product for playing back rail transit monitoring information, which can intuitively reflect the actual operating status of rail transit at that time, thereby improving the efficiency and accuracy of operation and management personnel in judging faults.

[0006] To achieve the above objectives, this application provides the following solution: Firstly, this application provides a method for playing back rail transit monitoring information, including: Read the target line number and playback time period from the received history playback command; Multiple historical rail transit data matching the line number and the review period are obtained from a pre-built time-series database table; wherein the historical collection time of the historical rail transit data is within the review period, and the historical rail transit data includes at least historical ATS train operation monitoring data, historical ATS equipment monitoring data, historical integrated monitoring system monitoring data, historical passenger flow monitoring data, and historical operation organization adjustment data; The historical rail transit data are output sequentially from morning to night according to the historical collection time.

[0007] Optionally, the method further includes: Collect the current ATS train operation monitoring data, current ATS equipment monitoring data, current integrated monitoring system monitoring data, current passenger flow monitoring data, current operation organization adjustment data, and the collection time corresponding to the current route number; Based on a preset data standard format, the current ATS driving monitoring data, the current ATS equipment monitoring data, the current integrated monitoring system monitoring data, the current passenger flow monitoring data, and the current operation organization adjustment data are standardized to obtain standard ATS driving monitoring data, standard ATS equipment monitoring data, standard integrated monitoring system monitoring data, standard passenger flow monitoring data, and standard operation organization adjustment data. The standard ATS train monitoring data, the standard ATS equipment monitoring data, the standard integrated monitoring system monitoring data, the standard passenger flow monitoring data, and the standard operation organization adjustment data are integrated to obtain the initial rail transit data for the current line. The current line number and the acquisition time are added to the initial rail transit data to obtain the standard rail transit data for the current line; The standard rail transit data is written into the time-series database table.

[0008] Optionally, the preset data standard format specifically includes data tags, data content, and data time; The data tags include line number, rail transit professional code, equipment type, equipment name, and information type.

[0009] Optionally, the data content in the standard ATS train operation monitoring data includes at least: line number, ATS central station number, train group number, train number, train dispatch number, train window number where the train is running, equipment name at the location where the train is running, equipment type at the location where the train is running, train deviation from the plan time, number of train formations, train destination code, train load factor, train speed, train status, and train operation data time.

[0010] Optionally, the data content in the standard ATS equipment monitoring data shall include at least: line number, ATS central station number, equipment type, equipment name, equipment status, equipment status value, and equipment monitoring data time.

[0011] Optionally, the step of outputting the multiple historical rail transit data in sequence from morning to evening according to the historical collection time specifically includes: The amount of cached data is determined based on the preset cache interval duration; Based on the cached data volume, historical rail transit data to be output is obtained from the multiple historical rail transit data in order of historical collection time from morning to evening; wherein, the number of historical rail transit data to be output is the same as the cached data volume; Based on a preset playback time interval, the historical rail transit data to be output is output sequentially from morning to night according to the historical collection time. If there are still unoutputted historical rail transit data in the multiple historical rail transit data sets, then the following steps are executed: from the cached data volume, the historical rail transit data to be output is obtained from the multiple historical rail transit data sets in order of historical collection time from earliest to latest, until the historical rail transit data to be output is output sequentially in order of historical collection time from earliest to latest based on the preset playback time interval.

[0012] Secondly, this application provides a rail transit monitoring information playback device, comprising: The reading unit is used to read the target line number and playback time period from the received historical playback command; The acquisition unit is used to acquire multiple historical rail transit data that match the line number and the review time period from a pre-built time-series database table; wherein the historical acquisition time of the historical rail transit data is within the review time period, and the historical rail transit data includes at least historical ATS train operation monitoring data, historical ATS equipment monitoring data, historical integrated monitoring system monitoring data, historical passenger flow monitoring data, and historical operation organization adjustment data; The output unit is used to output the multiple historical rail transit data in sequence from morning to night according to the historical collection time.

[0013] Thirdly, this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the rail transit monitoring information playback method described in any one of the above.

[0014] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the rail transit monitoring information playback method described above.

[0015] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the rail transit monitoring information playback method described above.

[0016] In a sixth aspect, this application provides a chip, the chip including a processor and a communication interface, the communication interface being coupled to the processor, the processor being used to run a program or instructions, and the processor executing the program or instructions implementing the steps of the rail transit monitoring information playback method described above.

[0017] According to the specific embodiments provided in this application, the following technical effects are disclosed: This application provides a method, device, equipment, medium, and product for playing back rail transit monitoring information. By reading the target line number and playback time period from a historical playback command, it accurately retrieves multiple matching historical rail transit data from a time-series database table. This data covers various aspects such as train operation, equipment, integrated monitoring, passenger flow, and operational adjustments, and the data collection time falls within the playback period. The data is then output sequentially according to the historical collection time. This method of integrating multiple key monitoring information and presenting it chronologically breaks the limitations of independent playback from different data sources. It can comprehensively and coherently display the entire operation of rail transit within a specific time period, allowing operation and management personnel to intuitively reflect the actual operating status of the rail transit at that time, quickly capture key information, and thus effectively improve the efficiency and accuracy of fault diagnosis. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 A flowchart illustrating a method for playing back rail transit monitoring information, provided as an embodiment of this application; Figure 2 A schematic diagram of the structure of a time-series database table provided in an embodiment of this application; Figure 3 A schematic diagram of standard rail transit data provided in an embodiment of this application; Figure 4 A schematic diagram illustrating the playback of rail transit monitoring information according to an embodiment of this application; Figure 5 A functional module diagram of a rail transit monitoring information playback device provided in an embodiment of this application; Figure 6 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0020] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0021] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0022] In one exemplary embodiment, such as Figure 1 As shown, a method for playing back rail transit monitoring information is provided. This method is executed by computer equipment, specifically by a terminal or server alone, or by both a terminal and a server. In this embodiment, it includes the following steps 101 to 103. Wherein: Step 101: Read the target line number and playback time period from the received historical playback command.

[0023] In this embodiment of the application, the target line number can be the target line number of the track line, which can be used to determine a unique track line.

[0024] As an optional implementation, the following steps may also be performed before step 101: Collect the current ATS train operation monitoring data, current ATS equipment monitoring data, current integrated monitoring system monitoring data, current passenger flow monitoring data, current operation organization adjustment data, and the collection time corresponding to the current route number; Based on a preset data standard format, the current ATS driving monitoring data, the current ATS equipment monitoring data, the current integrated monitoring system monitoring data, the current passenger flow monitoring data, and the current operation organization adjustment data are standardized to obtain standard ATS driving monitoring data, standard ATS equipment monitoring data, standard integrated monitoring system monitoring data, standard passenger flow monitoring data, and standard operation organization adjustment data. The standard ATS train monitoring data, the standard ATS equipment monitoring data, the standard integrated monitoring system monitoring data, the standard passenger flow monitoring data, and the standard operation organization adjustment data are integrated to obtain the initial rail transit data for the current line. The current line number and the acquisition time are added to the initial rail transit data to obtain the standard rail transit data for the current line; The standard rail transit data is written into the time-series database table.

[0025] This implementation method involves first collecting various current monitoring data and their collection times, then standardizing them according to a preset standard format to ensure data uniformity and facilitate subsequent management and analysis. The data is then integrated, and line numbers and collection times are added to form standard rail transit data, which is finally written into a time-series database table. This series of operations ensures the integrity and accuracy of the data from collection to storage, providing a reliable and orderly data foundation for subsequent historical playback based on this data, and helping to more accurately reflect the rail transit operation status.

[0026] In this embodiment of the application, the preset data standard format specifically includes data tags, data content, and data time.

[0027] For example, the default data standard format is as follows: { "tag": "lid.sys.devtype.dev.attr", / / Data tag "value": { / / Data content "attr1": "1", / / Data attribute 1 "attr2": "2", / / Data attribute 2 "attr3": "3", / / Data attribute 3 }, "time": "2025-09-15T18:41:24.150Z" / / Data time } The time attribute is a string type in ISO 8601 format. The tag is constructed according to the format "line number.specialty (rail transit specialty code, such as signal ATS, power POW, environmental control BAS, fire protection FAS).type.equipment.data name ("lid.sys.devtype.dev.attr")". The value is JSON type object data, which is expressed according to different business data types and is parsed and used in the symbol processing script of the integrated monitoring diagram.

[0028] The data tags include line number, rail transit professional code, equipment type, equipment name, and information type.

[0029] The standard ATS train monitoring data should include at least the following information: line number, ATS central station number, train group number, train number, train dispatch number, train window number where the train is running, name of equipment at the location where the train is running, type of equipment at the location where the train is running, time of deviation from the plan, number of train formations, destination code of the train, train load factor, train speed, train status, and train operation data time.

[0030] The data content in the standard ATS equipment monitoring data shall include at least the following: line number, ATS central station number, equipment type, equipment name, equipment status, equipment status value, and equipment monitoring data time.

[0031] For example, the JSON structure of standard ATS train monitoring data (taking train information, i.e., a type of real-time ATS data, as an example) is as follows: { "tag": "12.ats.train_indication.078.info", "value": { "line_id": "12", / / line number "rtu_id": "19", / / ATS central station number "group_id": "078", / / Train group number "global_id": "1166", / / Train number "train_id": "10", / / Train dispatch number "tcc_window": "19027", / / The window number of the train in question "dev_name": "T011219G", / / The name of the equipment at the train's location "dev_type": 99, / / Device type at the train's location "otp_time": "-20", / / Train deviation from schedule time (seconds) "rollingstock": "4", / / Number of train formations "destination_id": "12AL", / / Train destination code "rate": "255", / / Train load factor "speed": "54", / / Train speed "mode": "268763659", / / Train status "msg_time": "2025-09-15T18:41:24.150Z" / / Train operation data time }, "time": "2025-09-15T18:41:24.150Z" / / Data reception time } Furthermore, the JSON structure of standard ATS device monitoring data is as follows: { "tag": "12.ats.device_state.PF021220.info", "value": { "line_id": "12", "rtu_id": "19", "dev_type": 7, / / Device type "dev_name": "PF021220", / / Device name "dev_status": 3659, / / Device status "mode": "268763659", / / Device status value "msg_time": "2025-09-15T18:41:24.150Z" / / Device monitoring data time }, "time": "2025-09-15T18:41:24.150Z" } Furthermore, the JSON structure of the monitoring data from the standard integrated monitoring system is as follows: { "tag": "12.POW.1223.HL_201.ddiHL-CBPosition", "value": 2, / / Power switch status (two-point switch: 2 closed, 1 open) "time": "2025-09-15T18:41:24.150Z" } Furthermore, the JSON structure of standard passenger flow monitoring data is as follows: { "tag": "12.ats.pfv.1227.info", "value": { "line_id": "12", "station_id": "1227", / / station code "pfvIn": 25, / / Passenger flow entering the station "pfvOut": 19, / / Outbound passenger flow "pfvChg": 16, / / Passenger flow (only available at transfer stations) "msg_time": "2025-09-15T12:41:24.150Z" }, "time": "2025-09-15T12:41:24.150Z" } In addition, the JSON structure of the standard operating organization's adjusted data is as follows: { "tag": "12.oa.1227.seal.info", "value": { "line_id": "12", / / line code "station_id": "1227", / / station code "event_type": 1, / / Type: 1. Sudden event, 2. Service disruption, 3. Station closure, 4. Early termination, 5. Traffic control, 6. Closure, 12. Extended operation "event_status": 19, / / Operational adjustment status: 1 enabled, 0 ended "begin_time": "2025-09-15T12:41:24.150Z", / / start time "end_time": "2025-09-15T12:41:24.150Z" / / End time }, "time": "2025-09-15T12:41:24.150Z" } Please refer to the following: Figure 2 and Figure 3 , Figure 2 A schematic diagram of the structure of a time-series database table provided in an embodiment of this application; Figure 3 This is a schematic diagram of standard rail transit data provided in an embodiment of this application.

[0032] The line_code and system_code fields in the time series database table are added to facilitate querying of routes and majors; the time field corresponds to the time attribute in JSON, the tag field corresponds to the tag time series in JSON, and the value field corresponds to the value attribute in JSON. It is stored in JSON format and deserialized when the application system queries it.

[0033] The monitoring data for the current route number corresponding to the vehicle monitoring service is shown in Table 1: Table 1. Monitoring data of the current route number corresponding to the vehicle monitoring service.

[0034] In this embodiment of the application, the normalized data can be pushed to a message queue for monitoring (such as NATS or Kafka).

[0035] Step 102: Obtain multiple historical rail transit data that match the line number and the time period to be reviewed from a pre-built time-series database table.

[0036] The historical data collection time of the historical rail transit data is within the review period. The historical rail transit data includes at least historical ATS train operation monitoring data, historical ATS equipment monitoring data, historical integrated monitoring system monitoring data, historical passenger flow monitoring data, and historical operation organization adjustment data.

[0037] Step 103: Output the multiple historical rail transit data in order from morning to night according to the historical collection time.

[0038] In this embodiment, the vehicle monitoring page enters playback mode, and playback is performed after selecting the time period and speed.

[0039] For example, the monitoring page backend calculates pagination based on the playback time period, queries historical time-series data, buffers each page to the frontend, and then plays it. Each page polls 20 tags, totaling 2400 data entries, with one data entry every 5 seconds, allowing for 10 minutes of playback. After 10 minutes, the next batch of historical data is buffered again.

[0040] As an optional implementation, step 103, which outputs the multiple historical rail transit data in order of historical collection time from morning to evening, may include: The amount of cached data is determined based on the preset cache interval duration; Based on the cached data volume, historical rail transit data to be output is obtained from the multiple historical rail transit data in order of historical collection time from morning to evening; wherein, the number of historical rail transit data to be output is the same as the cached data volume; Based on a preset playback time interval, the historical rail transit data to be output is output sequentially from morning to night according to the historical collection time. If there are still unoutputted historical rail transit data in the multiple historical rail transit data sets, then the following steps are executed: from the cached data volume, the historical rail transit data to be output is obtained from the multiple historical rail transit data sets in order of historical collection time from earliest to latest, until the historical rail transit data to be output is output sequentially in order of historical collection time from earliest to latest based on the preset playback time interval.

[0041] This implementation method, by pre-setting the buffer interval to determine the amount of buffered data, can reasonably control the scale of data buffering and avoid resource waste. Acquiring the corresponding amount of data to be output according to historical collection times and outputting it sequentially according to the preset playback interval ensures a smooth and orderly playback process. Furthermore, cyclically executing the acquisition and output steps ensures complete playback of all historical rail transit data. This orderly and controllable output method allows operation and management personnel to view historical operation data more clearly and consistently, improving their ability to analyze and judge the operational status of rail transit.

[0042] Optionally, this application can also support 0.5× / 1× / 2× / 4× speed, pause, single frame step, and time axis dragging to quickly locate multiple historical rail transit data.

[0043] The embodiments of this application can also identify anomalies such as excessive train delays, sudden changes in equipment status, alarm information, and sudden increases in passenger flow in real time, highlighting, red-highlighting, and pop-up prompts on the playback interface, and automatically anchoring the time of the anomaly.

[0044] In this embodiment of the application, the rule for exceeding the train delay threshold can be: the absolute value of the difference between the planned running time and the actual running time of the train is greater than the preset delay threshold (such as 60 seconds, 120 seconds, 300 seconds); if the delay continues to increase for N consecutive data points, it is determined to be a deterioration of the delay.

[0045] The rules for sudden changes in equipment status can be: the equipment status changes abruptly (e.g., normal → fault, automatic → manual, off → on) at adjacent time points, or the equipment status value exceeds the normal range.

[0046] The alarm rules for the equipment can be: the data carries an alarm identifier, fault code, and alarm level; or the alarm status changes from "cleared" to "triggered", or from "normal" to "alarm".

[0047] The rules for sudden surges in passenger flow can be: the growth rate of passenger flow entering the station / transferring passengers compared to the previous period is greater than the preset threshold (such as 50% or 100%); or the absolute value of passenger flow exceeds the station's flow restriction threshold.

[0048] Operational adjustments can be triggered by events such as site closure, traffic restriction, site redirection, extended operation, and censorship, changing their status from "not enabled" to "enabled".

[0049] In this embodiment of the application, when outputting historical rail transit data point by point according to the historical collection time, the following can be executed simultaneously: 1. Parse the data type of the current data (ATS driving / ATS equipment / integrated monitoring / passenger flow / operational adjustment); 2. Extract key fields: Train operation data: delay time (otp_time), train status (mode), train number, and location; Device data: device status dev_status, status value mode, device name, alarm code; Passenger flow data: PfvIn (entry), PfvOut (exit), PfvChg (transfer); Operational data: event type (event_type) and event status (event_status).

[0050] 3. Send the current data to the anomaly detection engine, specifically: The anomaly detection engine matches corresponding rules based on the data type: 1. If it is ATS driving data: If |otp_time| > the late arrival threshold, then the late arrival is considered abnormal.

[0051] 2. If it is ATS equipment / integrated monitoring data: If the current state is inconsistent with the previous state and it is a jump, then the device state change is determined to be abnormal. If the data contains alarm flags / fault codes, it indicates that the device is alarming abnormally.

[0052] 3. If it is passenger flow data: If the current passenger flow value - the passenger flow value of the previous period / the passenger flow value of the previous period is greater than the growth rate threshold, then an abnormal surge in passenger flow is determined.

[0053] 4. If the data is adjusted for operational organization: If the event_status changes from 0 to 1 (from not enabled to enabled), it indicates that an operational adjustment has triggered an anomaly.

[0054] If any rule is met, immediately mark it as an anomaly at the current moment.

[0055] As an optional implementation method, related events can also be extracted in chronological order to form a complete fault chain of "event triggering → status change → operation adjustment → fault recovery". Clicking on an event node can directly jump to the corresponding time point.

[0056] In this embodiment of the application, the event triggering class may include: train delay exceeding the standard, equipment alarm, signal abnormality, power outage, sudden increase in passenger flow, communication interruption, etc.

[0057] Status change categories can include: equipment status jump, train mode change, area blockade, signal degradation, environmental control status change, etc.

[0058] Operational adjustments can include: station closures, passenger flow restrictions, skipping stations, closing off access points, adding / suspending trains, extending operating hours, and adjusting train intervals.

[0059] Fault recovery categories can include: alarm clearing, equipment returning to normal, delays being reduced, passenger flow decreasing, operational adjustments being cancelled, and routes returning to normal.

[0060] Adjacent time can be defined as the latter event occurring within a preset time window following the former event (e.g., 30 seconds to 5 minutes). The same object can refer to: the event pointing to the same train, the same equipment, the same station, or the same section; Logical correlations can be as follows: status changes are triggered by alarms, operational adjustments are triggered by status changes, and recovery is triggered by handling operations.

[0061] In this embodiment of the application, after acquiring multi-source historical rail transit data for a specified time period, the system traverses frame by frame from morning to night according to the acquisition time, and performs event identification and extraction for each data point: 1. For ATS driving data: extract events such as exceeding delay limits, abnormal location, and mode change; 2. For ATS equipment / integrated monitoring data: extract alarm triggering, status change, and alarm recovery events; 3. For passenger flow data: extract events such as sudden increases in passenger flow and exceeding passenger flow limits; 4. Data on operational organization adjustments: Extract adjustment initiation and cancellation events.

[0062] For each extracted event, a standardized event structure is generated, which includes: event timestamp, event type (trigger / change / adjustment / recovery), event object (train number / equipment name / station / section), event content description, and associated data ID.

[0063] The system automatically links independent events into a causal chain based on chronological order and association rules. The structure is fixed as follows: Event trigger → Status change → Operational adjustment → Fault recovery.

[0064] Specific construction logic: 1. The first alarm / abnormality / sudden increase in delays is used as the starting point of the fault chain (event trigger); 2. Connect subsequent state transitions of the same object into state change nodes; 3. Connect the subsequent operational adjustments, traffic restrictions, site closures, and site redirects into operational adjustment nodes; 4. Mark the last alarm clearing, status restoration, and delayed fallback as fault recovery nodes; 5. If multiple fault chains exist within the same time period, they will be displayed in groups by line / station / equipment.

[0065] Ultimately, this forms a timeline, a chain of causes and effects, and a complete diagram of the failure process.

[0066] The integrated monitoring and playback interface for rail transit displays the fault chain in a vertical timeline list, with each node containing: Time point (accurate to the second); Event icons (alarm / status / adjustment / recovery); Event severity color (red / orange / yellow / green); Brief description of the event; Related objects (trains / equipment / stations).

[0067] For example: 07:00:12 [Event Triggered] Train 078 is more than delayed (-120 seconds); 07:00:28 [Status Change] The status of signal device PF021220 changes from normal to abnormal; 07:01:45 [Operational Adjustment] Passenger flow control measures implemented at XX station on Line 12; 07:05:30 [Fault Recovery] The equipment status has returned to normal, and the delay will fall back to -20 seconds.

[0068] After playback is complete, a standardized debriefing report is automatically generated, including the playback time period, key events, abnormal information, data screenshots, and handling suggestions. It supports exporting to PDF / Excel.

[0069] Please refer to the following: Figure 4 , Figure 4 This is a schematic diagram illustrating the playback of rail transit monitoring information according to an embodiment of this application. Specifically, Figure 4 This is a schematic diagram of a rail transit monitoring information playback method for Metro Line 12.

[0070] By implementing steps 101 to 103 above, the target line number and playback time period are read from the historical playback command, and multiple matching historical rail transit data are accurately obtained from the time-series database table. This data covers various aspects such as train operation, equipment, integrated monitoring, passenger flow, and operational adjustments, and the data collection time falls within the playback period. The data is then output sequentially according to the historical collection time. This method of integrating multiple key monitoring information and presenting it chronologically breaks the limitations of independent playback from different data sources. It provides a comprehensive and coherent view of the rail transit operation within a specific time period, allowing operation managers to intuitively reflect the actual operation of the rail transit at that time, quickly capture key information, and effectively improve the efficiency and accuracy of fault diagnosis. Furthermore, this application ensures the integrity and accuracy of data from collection to storage, providing a reliable and orderly data foundation for subsequent historical playback based on this data, which helps to more accurately reflect the rail transit operation status. In addition, this application allows operation managers to view historical operation data more clearly and coherently, improving their ability to analyze and judge the rail transit operation status.

[0071] Based on the same inventive concept, this application also provides a rail transit monitoring information playback device for implementing the rail transit monitoring information playback method described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations of one or more rail transit monitoring information playback device embodiments provided below can be found in the limitations of the rail transit monitoring information playback method described above, and will not be repeated here.

[0072] In one exemplary embodiment, such as Figure 5 As shown, a rail transit monitoring information playback device is provided, comprising: The reading unit 501 is used to read the target line number and playback time period from the received historical playback command; The acquisition unit 502 is used to acquire multiple historical rail transit data that match the line number and the review time period from a pre-built time-series database table; wherein the historical acquisition time of the historical rail transit data is within the review time period, and the historical rail transit data includes at least historical ATS train operation monitoring data, historical ATS equipment monitoring data, historical integrated monitoring system monitoring data, historical passenger flow monitoring data, and historical operation organization adjustment data; The output unit 503 is used to output the multiple historical rail transit data in sequence from morning to night according to the historical collection time.

[0073] As an optional implementation, the reading unit 501 is also used for: Collect the current ATS train operation monitoring data, current ATS equipment monitoring data, current integrated monitoring system monitoring data, current passenger flow monitoring data, current operation organization adjustment data, and the collection time corresponding to the current route number; Based on a preset data standard format, the current ATS driving monitoring data, the current ATS equipment monitoring data, the current integrated monitoring system monitoring data, the current passenger flow monitoring data, and the current operation organization adjustment data are standardized to obtain standard ATS driving monitoring data, standard ATS equipment monitoring data, standard integrated monitoring system monitoring data, standard passenger flow monitoring data, and standard operation organization adjustment data. The standard ATS train monitoring data, the standard ATS equipment monitoring data, the standard integrated monitoring system monitoring data, the standard passenger flow monitoring data, and the standard operation organization adjustment data are integrated to obtain the initial rail transit data for the current line. The current line number and the acquisition time are added to the initial rail transit data to obtain the standard rail transit data for the current line; The standard rail transit data is written into the time-series database table.

[0074] This implementation method involves first collecting various current monitoring data and their collection times, then standardizing them according to a preset standard format to ensure data uniformity and facilitate subsequent management and analysis. The data is then integrated, and line numbers and collection times are added to form standard rail transit data, which is finally written into a time-series database table. This series of operations ensures the integrity and accuracy of the data from collection to storage, providing a reliable and orderly data foundation for subsequent historical playback based on this data, and helping to more accurately reflect the rail transit operation status.

[0075] In this embodiment of the application, the preset data standard format specifically includes data tags, data content, and data time; The data tags include line number, rail transit professional code, equipment type, equipment name, and information type.

[0076] The standard ATS train monitoring data should include at least the following information: line number, ATS central station number, train group number, train number, train dispatch number, train window number where the train is running, name of equipment at the location where the train is running, type of equipment at the location where the train is running, time of deviation from the plan, number of train formations, destination code of the train, train load factor, train speed, train status, and train operation data time.

[0077] The data content in the standard ATS equipment monitoring data shall include at least the following: line number, ATS central station number, equipment type, equipment name, equipment status, equipment status value, and equipment monitoring data time.

[0078] As an optional implementation, the output unit 503 may output the multiple historical rail transit data in sequence from morning to evening according to the historical collection time in the following ways: The amount of cached data is determined based on the preset cache interval duration; Based on the cached data volume, historical rail transit data to be output is obtained from the multiple historical rail transit data in order of historical collection time from morning to evening; wherein, the number of historical rail transit data to be output is the same as the cached data volume; Based on a preset playback time interval, the historical rail transit data to be output is output sequentially from morning to night according to the historical collection time. If there are still unoutputted historical rail transit data in the multiple historical rail transit data sets, then the following steps are executed: from the cached data volume, the historical rail transit data to be output is obtained from the multiple historical rail transit data sets in order of historical collection time from earliest to latest, until the historical rail transit data to be output is output sequentially in order of historical collection time from earliest to latest based on the preset playback time interval.

[0079] This implementation method, by pre-setting the buffer interval to determine the amount of buffered data, can reasonably control the scale of data buffering and avoid resource waste. Acquiring the corresponding amount of data to be output according to historical collection times and outputting it sequentially according to the preset playback interval ensures a smooth and orderly playback process. Furthermore, cyclically executing the acquisition and output steps ensures complete playback of all historical rail transit data. This orderly and controllable output method allows operation and management personnel to view historical operation data more clearly and consistently, improving their ability to analyze and judge the operational status of rail transit.

[0080] By implementing the above method, the target line number and playback time period are read from the historical playback command, and multiple matching historical rail transit data are accurately obtained from the time-series database table. This data covers various aspects such as train operation, equipment, integrated monitoring, passenger flow, and operational adjustments, and the data collection time falls within the playback period. The data is then output sequentially according to the historical collection time. This method of integrating multiple key monitoring information and presenting it chronologically breaks the limitations of independent playback from different data sources. It provides a comprehensive and coherent view of the rail transit operation within a specific time period, allowing operation managers to intuitively reflect the actual operation of the rail transit at that time, quickly capture key information, and effectively improve the efficiency and accuracy of fault diagnosis. Furthermore, this application ensures the integrity and accuracy of data from collection to storage, providing a reliable and orderly data foundation for subsequent historical playback based on this data, which helps to more accurately reflect the rail transit operation status. In addition, this application allows operation managers to view historical operation data more clearly and coherently, improving their ability to analyze and judge the rail transit operation status.

[0081] In one exemplary embodiment, a computer device is provided, which may be a server or a terminal, and its internal structure diagram may be as follows. Figure 6 As shown, the computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores playback data of rail transit monitoring information. The I / O interfaces are used for information exchange between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements a method for playback of rail transit monitoring information.

[0082] Those skilled in the art will understand that Figure 6 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0083] In one exemplary embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0084] In one exemplary embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0085] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0086] In one exemplary embodiment, a chip is provided, the chip including a processor and a communication interface, the communication interface being coupled to the processor, the processor being used to run programs or instructions to implement the steps in the above method embodiments and achieve the same technical effect, and will not be described again here to avoid repetition.

[0087] It should be understood that the chip mentioned in the embodiments of this application may also be referred to as a system-on-a-chip, system chip, chip system, or system-on-a-chip, etc.

[0088] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0089] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0090] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0091] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0092] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for playing back rail transit monitoring information, characterized in that, The method for playing back rail transit monitoring information includes: Read the target line number and playback time period from the received history playback command; Multiple historical rail transit data matching the line number and the review period are obtained from a pre-built time-series database table; wherein the historical collection time of the historical rail transit data is within the review period, and the historical rail transit data includes at least historical ATS train operation monitoring data, historical ATS equipment monitoring data, historical integrated monitoring system monitoring data, historical passenger flow monitoring data, and historical operation organization adjustment data; The historical rail transit data are output sequentially from morning to night according to the historical collection time.

2. The method for playing back rail transit monitoring information according to claim 1, characterized in that, The method further includes: Collect the current ATS train operation monitoring data, current ATS equipment monitoring data, current integrated monitoring system monitoring data, current passenger flow monitoring data, current operation organization adjustment data, and the collection time corresponding to the current route number; Based on a preset data standard format, the current ATS driving monitoring data, the current ATS equipment monitoring data, the current integrated monitoring system monitoring data, the current passenger flow monitoring data, and the current operation organization adjustment data are standardized to obtain standard ATS driving monitoring data, standard ATS equipment monitoring data, standard integrated monitoring system monitoring data, standard passenger flow monitoring data, and standard operation organization adjustment data. The standard ATS train monitoring data, the standard ATS equipment monitoring data, the standard integrated monitoring system monitoring data, the standard passenger flow monitoring data, and the standard operation organization adjustment data are integrated to obtain the initial rail transit data for the current line. The current line number and the acquisition time are added to the initial rail transit data to obtain the standard rail transit data for the current line; The standard rail transit data is written into the time-series database table.

3. The method for playing back rail transit monitoring information according to claim 2, characterized in that, The preset data standard format specifically includes data tags, data content, and data time. The data tags include line number, rail transit professional code, equipment type, equipment name, and information type.

4. The method for playing back rail transit monitoring information according to claim 3, characterized in that, The data content in the standard ATS train operation monitoring data includes at least the following: line number, ATS central station number, train group number, train number, train dispatch number, train window number where the train is running, equipment name at the location where the train is running, equipment type at the location where the train is running, train deviation from the plan time, number of train formations, train destination code, train load factor, train speed, train status, and train operation data time.

5. The method for playing back rail transit monitoring information according to claim 2, characterized in that, The data content in the standard ATS equipment monitoring data includes at least: line number, ATS central station number, equipment type, equipment name, equipment status, equipment status value, and equipment monitoring data time.

6. The method for playing back rail transit monitoring information according to claim 1, characterized in that, The step of outputting the multiple historical rail transit data in sequence from morning to night according to the historical collection time specifically includes: The amount of cached data is determined based on the preset cache interval duration; Based on the cached data volume, historical rail transit data to be output is obtained from the multiple historical rail transit data in order of historical collection time from morning to evening; wherein, the number of historical rail transit data to be output is the same as the cached data volume; Based on a preset playback time interval, the historical rail transit data to be output is output sequentially from morning to night according to the historical collection time. If there are still unoutputted historical rail transit data in the multiple historical rail transit data sets, then the following steps are executed: from the cached data volume, the historical rail transit data to be output is obtained from the multiple historical rail transit data sets in order of historical collection time from earliest to latest, until the historical rail transit data to be output is output sequentially in order of historical collection time from earliest to latest based on the preset playback time interval.

7. A rail transit monitoring information playback device, characterized in that, The rail transit monitoring information playback device includes: The reading unit is used to read the target line number and playback time period from the received historical playback command; The acquisition unit is used to acquire multiple historical rail transit data that match the line number and the review time period from a pre-built time-series database table; wherein the historical acquisition time of the historical rail transit data is within the review time period, and the historical rail transit data includes at least historical ATS train operation monitoring data, historical ATS equipment monitoring data, historical integrated monitoring system monitoring data, historical passenger flow monitoring data, and historical operation organization adjustment data; The output unit is used to output the multiple historical rail transit data in sequence from morning to night according to the historical collection time.

8. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the steps of the rail transit monitoring information playback method according to any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the rail transit monitoring information playback method according to any one of claims 1-6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the rail transit monitoring information playback method according to any one of claims 1-6.

Images